Amazon AI pushes into enterprise software with AI agents for supply chain, hiring, and productivity

Amazon unveils a Copilot for all your apps

Retailer touts 'teammates' and always-on context as it muscles into an already crowded enterprise market Amazon has announced two AI services pitched with typical techbro hyperbole, aimed at changing the way you work. The first is "a new experience" for Amazon Quick, taking direct aim at Microsoft Copilot and its ilk, only across a wide variety of software. It requires an email address to get started and a new desktop app that, in Amazon's words, "lives on your computer and connects directly to your work." No AWS account is needed, though it will need authentication with other services to get the most out of it. Amazon notes that native integrations with Google Workspace, Microsoft 365, Zoom, and Salesforce are present. The suite, first unveiled in October 2025, was a web-based experience intended to simplify building agents. It includes proactive alerts and always-on context, and the tool can be used to create apps, such as an HR onboarding portal or a pipeline health monitor for the sales team. At an event in San Francisco on Tuesday, Amazon Quick VP Jigar Thakkar said, "Every day you lose hours to work that actually does not need you there ... Amazon Quick built to give you that time back." He gave an example of setting up a meeting for a project - instead of checking everybody's calendars and sending messages over email, Slack, and multiple other platforms, you just send one prompt via the Quick desktop app: Set up a meeting for project x. It knows who needs to be there, who's busy, who's free, figures out the time, and sends the invite automatically. It's able to do this because every time you use Quick, it studies what you're doing and stores that context, such as project deadlines, other participants, and so on. When quizzed about the security implications of having a model watching and storing your every move, Thakkar simply pointed to AWS's 20-year-plus history of providing secure cloud services. We're sure there'll be detailed documentation to clarify this hand-wave at some future point. The second service is a significant overhaul of Amazon Connect, which expands from a single product into four agentic AI components: Connect Decisions for supply chains, Connect Talent for hiring (the company demonstrated a job interview conducted by an AI chatbot, which is a depressing glimpse of the future of work), Connect Health for healthcare, and Connect Customer AI - a rebrand of the original service - focused on customer experience. Amazon Connect was launched by AWS in 2017 as a cloud-based contact center tech to let businesses establish and manage customer service ops themselves. "It began as the technology powering Amazon's retail customer service, and we've spent years learning how to run it at scale," the company said. Each solution comprises a set of AI agents, or "teammates," to take care of business, although Amazon insists it is the user who remains in control. The market for AI agents running business processes is crowded. Salesforce has staked out its agents everywhere vision, albeit while recovering from a now-patched vulnerability where Agentforce could be tricked into leaking sales data. Similarly, Google offers Gemini Enterprise for workflow automation. Microsoft has gone all in with a new Microsoft 365 tier with features including Agent 365, a dedicated control plane for AI agents. Amazon will need to work hard to pry customers away from vendors they're already embedded with. ®

Amazon Launches AI Productivity Software for Office Workers

Amazon.com Inc.'s cloud unit, best known for providing technology infrastructure to corporations, is looking to sell AI-powered productivity software for the office. Amazon Web Services on Tuesday announced a set of tools - aimed at logistics workers and recruiters - called Amazon Connect Decisions and Amazon Connect Talent. Together with a suite of health applications introduced last month, the products telegraph Amazon's determination to use its artificial intelligence technology to break into the business software market. Gartner, the technology researcher, estimates that companies spent roughly $300 billion on software-as-a-service products in 2025, a category that includes products to help track and manage sales, personnel and planning. Amazon, the largest seller of web infrastructure including rented data storage and processing power, barely registers in that market. But the advent of AI models has given the company an opportunity to offer something new, said AWS Chief Marketing Officer Julia White. The products announced this week rely on AI agents, the industry term for tools that can take action on a user's behalf, whether to conduct an automated interview with a job candidate or create a spreadsheet forecasting demand for a product. "We don't have a big legacy of SaaS or, frankly, a franchise to protect," White said in an interview ahead of the product announcement on Tuesday at an event in San Francisco. "It allows us to really embrace this agentic-first approach in a way that is going to be harder for other people." The new products put Amazon into deeper competition with cloud rivals like Microsoft Corp. and Oracle Corp., as well as some of its biggest customers, including Salesforce Inc. That's not a new position for Amazon, which has spent years assuring the likes of Netflix - built on AWS but a fierce rival of Amazon's Prime Video - that it's an ethical competitor. AWS has been reluctant to commit to building a broad suite of business applications, occasionally spooking rivals with one-off products like email server management tools or supply-chain software, but stopping short of the sort of concerted push announced this week. The company has said in the last few years that it would wind down document-sharing, email and video-calling services. AWS's biggest hit, Amazon Connect, a product for call center and support workers, last year was on track to reap $1 billion in sales over the course of a year. On Tuesday, Amazon renamed the product Amazon Customer Connect. "We already have deep relationships with many people in these industries, so it's a pretty natural fit," White said.

Amazon tried selling office software and failed. Now it is betting that office software itself is obsolete.

Amazon Web Services announced a set of AI-powered business applications on Tuesday that move the company from selling cloud infrastructure to selling the software that runs on it, a strategic shift that puts Amazon in direct competition with Microsoft, Oracle, and Salesforce in the $300 billion software-as-a-service market. The new products, Amazon Connect Decisions for supply chain management and Amazon Connect Talent for recruitment, join Amazon Connect Health, a healthcare agent platform launched in March, to form an expanding portfolio of AI-native business tools built on the same agentic architecture. AWS also renamed its flagship call centre product from Amazon Connect to Amazon Customer Connect, a rebranding that signals the company views its contact centre business, which hit a $1 billion annualised revenue run rate in 2025, as the foundation of a broader enterprise software strategy rather than a standalone product. "We don't have a big legacy of SaaS or, frankly, a franchise to protect," said Julia White, AWS's chief marketing officer. "It allows us to really embrace this agentic-first approach in a way that is going to be harder for other people." Amazon Connect Decisions is a supply chain optimisation platform that draws on more than 25 internal tools Amazon built for its own logistics operations, including the SCOT foundation models that power Amazon's demand forecasting. The product uses AI agents to generate and tune demand forecasts, triage supply chain alerts, perform root-cause analysis, and create scenario-planning spreadsheets. The target user is a supply chain planner, not a data scientist, and the product is designed to compress workflows that currently require multiple specialised applications into a single agent-driven interface. Amazon Connect Talent conducts autonomous voice-based job interviews around the clock, scoring candidates on skills rather than resumes, and is aimed at high-volume hiring in manufacturing, logistics, retail, and hospitality. The platform schedules, calls, and interviews candidates without human intervention, making it the first AWS offering where an AI agent autonomously initiates and conducts real-time voice conversations on the company's behalf. Amazon Connect Health, which became generally available on March 5, delivers five AI agents for patient identity verification, appointment scheduling, medical history summaries, clinical notes, and medical coding, priced at $99 per user per month. Together, the three Connect products share a common pattern: Amazon takes an operational capability it built for its own business, retail logistics, high-volume hiring, healthcare management through Amazon Clinic and One Medical, abstracts it into an AI-native product, and sells it to enterprises through AWS. The approach is not new for Amazon, which has spent decades turning internal infrastructure into cloud services, but the application layer is. The $285 billion SaaS market anxiety that rattled software stocks in February reflects a genuine uncertainty about whether AI agents will replace traditional per-seat software or simply augment it. Amazon is betting on replacement, but only in categories where it has operational expertise that incumbents lack. The new products put AWS into a competitive posture it has historically avoided. Amazon spent years assuring enterprise customers, including companies like Netflix that competed directly with Amazon's consumer businesses while running their infrastructure on AWS, that it would not use its cloud position to undercut their software. AWS had been reluctant to commit to a broad business application suite, occasionally launching one-off products like WorkMail for email, Chime for video conferencing, and WorkDocs for document sharing, only to wind all three down after they failed to gain traction. WorkDocs shut down in April 2025. Amazon Chime was discontinued in February 2026. WorkMail ends support in March 2027. The previous generation of AWS application products failed because they tried to compete with Microsoft on Microsoft's terms: generic productivity tools sold to knowledge workers. The new generation competes on Amazon's terms: specialised operational tools sold to frontline workers in categories where Amazon has built the best internal systems in the world. Microsoft's largest-ever enterprise Copilot deployment at Accenture, which rolled out to all 743,000 employees with an 89 per cent monthly active usage rate, demonstrates the scale of the incumbent advantage AWS must overcome in the knowledge worker market. Microsoft has 450 million enterprise Microsoft 365 users, each of whom represents a potential Copilot upsell. Oracle's Fusion Cloud applications and Salesforce's Agentforce platform both have deep enterprise installation bases and years of customer workflow data. AWS has none of that. What it has is the largest cloud infrastructure customer base in the world and the operational expertise of the company that runs the most complex logistics network on Earth. The strategic logic is that AI agents do not need an existing software install base the way traditional SaaS does, because the agent replaces the application rather than sitting inside it. If that logic holds, AWS's infrastructure relationships become the distribution channel and Amazon's operational IP becomes the competitive moat. If it does not hold, the Connect products become the next WorkMail: ambitious launches that fade when enterprise customers choose to add AI capabilities to the software they already use rather than replace it. AWS also announced Amazon Quick, a separate AI copilot that works across Google Workspace, Microsoft 365, Zoom, and Salesforce without requiring an AWS account, a product that takes direct aim at Microsoft Copilot's cross-application integration. The breadth of announcements at the "What's Next with AWS" event in San Francisco signals a coordinated strategy, not a collection of experiments. Anthropic's zero-commission Claude Marketplace for enterprise software demonstrates that even foundation model companies are now building their own enterprise app distribution platforms, modelling them on the marketplace architecture that AWS pioneered. The competitive landscape for enterprise AI is no longer a three-way fight between hyperscalers. It is a multi-front contest in which cloud providers, AI labs, and incumbent software companies are all attempting to own the layer between the model and the business workflow. Gartner estimates that companies spent roughly $300 billion on SaaS products in 2025. The symbolic death of SaaS as a category, marked by the retirement of Europe's largest SaaS conference brand in favour of an AI-focused successor, reflects the industry's belief that the per-seat, per-application model is giving way to an agent-driven model where value concentrates in the orchestration layer rather than the application itself. Amazon's bet is that the company best positioned to win that orchestration layer is the one that already runs the infrastructure underneath it. White's acknowledgement that AWS has no SaaS legacy to protect is both an admission of past failure and a claim of strategic advantage: the company that could not beat Microsoft at productivity software is arguing that productivity software itself is being replaced, and that the replacement favours the infrastructure provider with the best operational data and the broadest customer base. Google's full-stack agentic AI play at Cloud Next 2026, which rebranded Vertex AI into the Gemini Enterprise Agent Platform with a no-code agent builder, makes the same argument from a different direction. The three largest cloud providers have converged on the same thesis at the same moment: that AI agents will eat SaaS. The question is whether the enterprises writing the cheques agree, or whether they will do what enterprises have always done and add AI to their existing software rather than replace it.

AWS turns Amazon's hiring and supply chain expertise into new AI products for other businesses

SAN FRANCISCO -- Amazon manages more than 400 million products in its supply chain and hired 250,000 seasonal workers last peak season. Now its cloud division is packaging up what the company has learned and getting ready to sell it to other businesses. Amazon Web Services on Tuesday announced two new agentic AI products: Connect Decisions, which uses Amazon's own supply chain models to help companies forecast demand and manage disruptions; and Connect Talent, which conducts voice-based job interviews around the clock and scores candidates on skills rather than resumes. They're part of a growing lineup of AWS business applications, which started with the Amazon Connect contact-center platform in 2017, which has since become a billion-dollar business. The lineup expanded more to health care with Connect Health, announced last month. AWS event: Amazon is announcing the products at an event in San Francisco where AWS CEO Matt Garman is expected to detail the company's expanded work with OpenAI, following Monday's news that OpenAI's models will be available on Amazon Bedrock for the first time. That was made possible by a revamped deal between Microsoft and OpenAI, and builds on Amazon's earlier investment of up to $50 billion in the ChatGPT maker. Separately, AWS is releasing a major update to Amazon Quick, its AI assistant for business users, adding a desktop app, the ability to create custom dashboards and portals, and expanded integrations with Google Workspace, Microsoft 365, Zoom, and Salesforce. Expanded footprint: The new Connect apps push AWS further beyond cloud infrastructure and into direct competition with enterprise software companies, including some AWS customers. Colleen Aubrey, AWS senior vice president of Applied AI Solutions, acknowledged that selling applications that compete with AWS customers is "a newer dynamic" for the cloud business. However, she noted that it's familiar territory for Amazon overall. She compared it to the way the company sells its own products alongside third-party sellers on its marketplace, or produces original content for Prime Video while also distributing shows from other studios. Aubrey called the new apps "a day zero" moment for the AWS applications team after spending the past two years assembling the group and doing the work to determine where to focus. "If we're lucky, we'll have some hits in this collection of four," she said in an interview, acknowledging that building enterprise software products is inherently uncertain. Asked why companies wouldn't simply build these capabilities themselves using AWS tools like Bedrock, Aubrey said the complexity of transforming an entire business function, not just an individual task, calls for a purpose-built product that can be used across an organization. Amazon's new Connect apps: Connect Decisions draws on more than 25 specialized supply chain models and tools, including one of Amazon's own foundation models built by its Supply Chain Optimization Technologies (SCOT) team. When something goes wrong in a supply chain -- a supplier falls behind, or demand spikes unexpectedly -- it can figure out what happened, rank the problems that need human attention, and suggest what to do about them, along with the cost and trade-offs of each option. Connect Talent is aimed at high-volume hiring in industries like manufacturing, logistics, retail, and hospitality, rather than corporate recruiting. AI agents conduct voice interviews that candidates can take anytime, eliminating scheduling conflicts. The system strips names and resumes from the process; recruiters see anonymized competency scores and transcripts. One early customer has started bringing Connect Decisions into business meetings to run what-if scenarios in real time, Aubrey said. That company's procurement team has already asked to expand its use beyond supply chain planning, which AWS ultimately plans to do.

Amazon's OpenAI gambit signals a new phase in the cloud wars -- one where exclusivity no longer applies

Amazon Web Services on Tuesday launched one of the most consequential enterprise AI plays in the company's 20-year history, simultaneously bringing OpenAI's most powerful models to its Bedrock platform, unveiling a new agentic developer framework, releasing a desktop AI productivity tool called Amazon Quick, and expanding its Amazon Connect service from a single contact-center product into a family of four agentic AI solutions targeting supply chains, hiring, healthcare, and customer experience. The announcements, made at a live event in San Francisco titled "What's Next with AWS," landed just 24 hours after OpenAI and Microsoft publicly restructured their exclusive cloud partnership -- a move that, for the first time, freed OpenAI to distribute all of its products across rival cloud providers. AWS CEO Matt Garman called it "a huge partnership" and said customers have been asking for OpenAI models inside AWS "from the very early days." The timing was no accident. Amazon CEO Andy Jassy had flagged the Microsoft-OpenAI restructuring as "very interesting" in a post on X the day prior, promising more details on Tuesday. What followed was a sweeping set of launches that together represent AWS's bid to become the definitive infrastructure layer for the agentic AI era -- one where intelligent software agents don't just answer questions but take autonomous action inside enterprise workflows. OpenAI's most capable models arrive on Amazon Bedrock for the first time, reshaping the cloud AI marketplace The centerpiece announcement: OpenAI's latest models are now available through Amazon Bedrock in limited preview, with general availability expected within weeks. AWS confirmed that GPT-5.4 is available immediately in limited preview, with GPT-5.5 arriving shortly thereafter. In an exclusive interview with VentureBeat at the event, Anthony Liguori, Vice President and Distinguished Engineer at AWS, described the significance of the moment. "We announced a partnership about eight weeks ago centered around this idea of the stateful runtime environment, the SRE APIs," Liguori said. "However, today we announced the availability of all of OpenAI's frontier models in Amazon Bedrock available via both the stateless APIs -- these are the APIs that are commonly used, like chat completions and responses." Liguori characterized the stateless API availability as particularly critical because it removes migration friction. "Customers can take their existing workloads today and just start using AWS right off the bat," he said. "They don't have to write any new software, develop any new things. I think that's one of the most exciting announcements that came out today." The integration means AWS customers can now evaluate and deploy OpenAI models alongside offerings from Anthropic, Meta, Mistral, Cohere, and Amazon's own models -- all through Bedrock's unified security, governance, and cost controls. For enterprise procurement teams, this collapses what had been a fragmented multi-vendor landscape into a single pane of glass. How a $50 billion Amazon investment and a messy Microsoft breakup cleared the way for Tuesday's deal The path to Tuesday's announcement was anything but smooth. As TechCrunch reported, OpenAI's earlier $50 billion deal with Amazon, announced in February, had created a legal tangle with Microsoft. Under the original Microsoft-OpenAI agreement, Microsoft retained exclusive rights to OpenAI products accessed through APIs, which appeared to conflict directly with OpenAI's promise to give AWS exclusive hosting rights for its new Frontier agent-building tool. Microsoft had publicly pushed back at the time, stating that "Azure remains the exclusive cloud provider of stateless OpenAI APIs." The Financial Times reported that Microsoft even contemplated legal action. Monday's restructured deal -- which replaced Microsoft's open-ended exclusivity with a nonexclusive license running through 2032 -- swept those legal obstacles aside. For AWS, the resolution means its multi-billion-dollar investment in OpenAI can now fully bear fruit. As CNBC reported, OpenAI's revenue chief Denise Dresser had told employees in a memo that the Microsoft relationship "has also limited our ability to meet enterprises where they are -- for many that's Bedrock." At the San Francisco event, Dresser framed the moment as a turning point. "They're no longer in the mindset of experimentation and pilots," she said of enterprise customers. "They really want to go full enterprise wide, and they understand that to do that, they need to have powerful models. But even more importantly, they want those models in a trusted environment." OpenAI CEO Sam Altman, who was unable to attend in person due to his ongoing court case against Elon Musk across the Bay Bridge in Oakland, sent a recorded video message. "We are co-developing an agent platform from the ground up, deeply integrated with AWS services and powered by OpenAI's most advanced models and tools," Altman said, "so that customers can build and run powerful agents in their own environment without worrying about the underlying plumbing." Inside Bedrock managed agents, the reinforcement learning-trained 'harness' that AWS says will define the agentic era Beyond raw model access, AWS launched Amazon Bedrock Managed Agents powered by OpenAI -- a system that combines OpenAI's frontier models with its proprietary "harness," the agentic execution framework that powers products like Codex. This is where Liguori's technical analysis was most revealing. He explained that the harness concept represents a shift in how models are trained and deployed for agentic work. "When you think about an agentic platform, there's really two components," Liguori told VentureBeat. "One is the harness -- the actual logic that will execute tool calls for the model, determine when to compact the context, all of those sorts of things -- and then the model itself." Critically, Liguori argued, the best agentic performance comes when models are trained specifically against their harness through reinforcement learning -- not merely prompted to use tools at inference time. "You can give a model a whole lot of instructions and a set of tools, and it will be able to use it most of the time," he said. "But when you really train the model on a specific set of tools, a specific style of operations, it's just like drilling plays over and over again -- the model builds muscle memory for using that harness." The football analogy is instructive. Where general-purpose models are like versatile athletes who can adapt to any playbook, harness-trained models are like championship teams that have run the same formations thousands of times until execution becomes instinctive. For enterprises deploying agents in high-stakes production environments -- managing financial transactions, orchestrating supply chains, or processing sensitive healthcare data -- that reliability gap matters enormously. Bedrock Managed Agents consists of three components: a runtime layer for configuring skills, memory policies, and tool access; an environment layer where the agent lives (deployable on Fargate or other AWS compute); and an inference API for interacting with the agent. The system integrates deeply with AWS's identity and access management, VPC networking, and CloudTrail auditing -- meaning every action an agent takes is logged and governed by existing enterprise security policies. AWS makes its boldest security claim yet: zero human access to inference machines running OpenAI's models Liguori made what may be his most striking claim when discussing why enterprises should trust AWS over on-premises alternatives or smaller cloud providers. "With Bedrock, the system that we're using to host the GPT-5.4 models, that whole environment is zero operator access," he told VentureBeat. "There's no human that could ever log into one of those machines, so your inference data is never able to be accessed by a human." He pointed to AWS's custom silicon -- Graviton processors and Nitro security chips -- as the foundation for this claim. "When you look at one of our servers, either compute servers or the servers we're using for Gen AI, the only thing that you can buy off the shelf is the memory modules. Everything else is either custom boards or even custom silicon." This argument is designed to counter a growing narrative from what the industry calls "neo-clouds" -- smaller providers that offer on-premises model hosting with tighter physical security controls. Liguori flipped that argument on its head: "You're actually way more secure in the cloud because we have built a platform with such strong physical securities... If you were to try to stand up your own inference system today, you'd probably be running open source software on just Linux." It's a bold claim, and one that enterprise CISOs will undoubtedly scrutinize. But it underscores AWS's conviction that the agentic era -- where AI agents access source code, PII data, and critical business systems -- demands infrastructure security guarantees that go far beyond what most organizations can build independently. Codex's 4 million weekly users could soon multiply as OpenAI's coding agent arrives on AWS OpenAI's Codex coding agent also arrived on Bedrock in limited preview. Dresser shared that Codex has been growing at a blistering pace, expanding "from 3 million weekly active users to 4 million in two weeks." The tool has evolved beyond simple code generation into a full agentic software development lifecycle platform. For Liguori, who described himself as "10 to 20 times more productive" as an engineer thanks to tools like Codex, bringing this capability into AWS represents the bridge between individual developer productivity and enterprise-scale deployment. "Most developers today are using these OpenAI models on their laptops," he said. "We haven't seen that happen yet in the rest of the industry, and with Bedrock Managed Agents, we think we have a way for enterprises to deploy agents in a means that meets their compliance requirements." The gap Liguori is describing -- between the solo developer experience and enterprise-wide adoption -- is arguably the central challenge of the current AI moment. Individual engineers can achieve extraordinary productivity gains with agentic coding tools. But scaling that to thousands of developers across a Fortune 500 company, with proper governance, security, and auditability, requires platform-level infrastructure. That's the market AWS is targeting. Liguori saw the near-term potential in even more immediate terms. He described leading a team of about 20 engineers who share a common codebase of skills and MCP tools. "That has been an amazingly powerful thing, because we're all able to build on top of each other as we learn how to use these models," he said. "Where I've run into a hurdle is there's a lot of stuff I'd like to share with our finance team... and I can't really ask them to clone a Git repo and build it from a Git repo." Bedrock Managed Agents, he argued, will let teams create hosted agents that non-technical colleagues can access -- taking agentic development from a developer-only practice to an enterprise-wide capability within the next six months. Amazon Quick Desktop aims to be the agentic AI assistant that finally works for non-developers While the OpenAI partnership dominated headlines, AWS also launched Amazon Quick Desktop -- a new desktop application designed to bring agentic AI to knowledge workers who aren't developers. Liguori framed the product as addressing a critical gap. "A lot of these agentic tools have primarily targeted developers," he said. "Quick Desktop is a really great tool if you are a knowledge worker that is not a developer... I think it's been underserved for the non-developer knowledge workers." Quick Desktop integrates with a user's local files, calendar, email, Slack, and enterprise applications -- building what AWS calls a "Knowledge Graph" that maps relationships between people, projects, decisions, and actions. The system connects natively with Google Workspace, Microsoft 365, Zoom, and Salesforce. Unlike other AI productivity tools, Quick doesn't wait for prompts. It proactively surfaces what matters -- unanswered emails, deals needing updates, documents awaiting review -- and can take action like scheduling meetings, drafting emails, or updating Jira tickets. Garman, who said he had been using the desktop app for several weeks, called it "by far the most effective tool" among AI productivity products he has tested. "If you think about what we've done with Quick -- combine all of your sources of data inside of the enterprise -- but then we also saw the power of having access to a local desktop and being able to operate with your local files and your local email and your local Slack... but people were worried about security, appropriately so," Garman said. "What we're doing here is combining a bunch of those things together with QUIC to give you the best of all of those worlds." The product is available in preview today, with no AWS account required -- users can sign up with just an email address. Customers including BMW, 3M, Mondelēz, Southwest Airlines, and the NFL are already using it, with some reporting production time reductions of nearly 80% and customer issue processing cut by more than 50%. Amazon Connect becomes a family of four as AWS bets that 'agentic teammates' will transform supply chains, hiring, and healthcare Perhaps the most ambitious long-term bet announced Tuesday was the expansion of Amazon Connect from a single contact-center product -- one that reached over $1 billion in revenue last year and processes 20 million interactions daily -- into a family of four agentic AI solutions. The new lineup includes Amazon Connect Decisions, an agentic supply chain planning tool built on more than 25 specialized supply chain tools and 30 years of Amazon operational science, including one of Amazon's SCOT (Supply Chain Optimization Technologies) foundation models. Amazon Connect Talent is a high-volume hiring platform inspired by Amazon's experience hiring 250,000 seasonal employees during peak periods, using AI agents to conduct voice interviews around the clock and present recruiters with anonymized, skills-based scoring. Amazon Connect Customer AI is the renamed and enhanced version of the original contact-center service. And Amazon Connect Health covers the patient journey from appointment scheduling through clinical encounters, including ambient documentation, billing code suggestions, and post-visit summaries drawn from Amazon's experience with One Medical and Amazon Pharmacy. Colleen Aubrey, who leads applied AI solutions at AWS and previously co-founded Amazon's advertising business, introduced a new design philosophy underlying all four products: "humorphism." Where skeuomorphism translated physical objects into digital metaphors -- desks to desktops, files to folders -- humorphism translates human interaction dynamics into AI agent behavior. "If we're building products that at the heart of which is an agentic teammate, then how should those teammates interact with you?" Aubrey asked. The philosophy manifests in specific design choices: Connect Decisions agents ask planners why they made manual adjustments and apply those insights across similar products. Connect Talent agents adapt follow-up questions based on candidate responses. Connect Health agents trace every clinical insight back to source data so physicians can verify AI-generated documentation. What AWS's four-layer strategy reveals about where the real value in enterprise AI will be captured Taken together, Tuesday's announcements reveal a coherent strategy operating across four distinct layers: custom infrastructure (Graviton, Trainium, zero-operator-access security), model access (Bedrock as a model marketplace with unified APIs), an agentic platform (Bedrock Managed Agents and AgentCore for building and governing agents), and purpose-built applications (Quick for individual productivity, Connect for vertical business operations). This layered approach addresses a fundamental tension in the enterprise AI market. Companies want choice at the model layer but integration at the platform layer and specificity at the application layer. By offering all three through a single security and governance framework, AWS is betting it can capture value across the entire stack -- a strategy that reshapes competitive dynamics for Microsoft, Google Cloud, and the growing constellation of smaller AI infrastructure providers. Garman pushed back on the "SaaSpocalypse" narrative that agentic AI will destroy incumbent enterprise software companies. "The incumbent providers today have such a huge advantage," he said. "They have deep domain expertise... a large customer set with all of their data." He pointed to Salesforce's recent headless API offering as an example of incumbents adapting smartly. But he also drew an explicit parallel to the early days of cloud computing, when customers would simply replicate their on-premises data centers in the cloud rather than reimagine what was possible. "You see that today with how people are thinking about AI and agents," Garman said. "They're like, 'I have this business process, I'm gonna have agents do the exact same thing that humans do.' It kind of works... but it doesn't give you that transformational change." He pointed to Amazon's own Prime Video team as proof of what that change looks like in practice. The team used agentic tools to rebuild a partner payment system that was projected to take two years -- completing it in roughly two quarters with a handful of people, while simultaneously improving the system for customers, for Amazon, and for the partners who get paid through it. The enterprise AI arms race enters a new phase as model access becomes table stakes and the platform war begins For enterprises evaluating their AI strategies, Tuesday's announcements simplify one decision -- OpenAI models are now available where most of them already run production workloads -- while complicating another. With model access increasingly commoditized across cloud providers, the real differentiator becomes the platform layer: where agents are built, governed, deployed, and trusted to take consequential actions. That's the battleground AWS is staking out, and it's the same ground Microsoft, Google, Salesforce, and a growing number of startups intend to contest. Liguori sees the transformation accelerating fast. "I think what we're going to see in the next six months is a lot of this agentic stuff going from developer only to being able to be consumed by a larger number of folks within an enterprise," he told VentureBeat. Anthony Liguori, the AWS distinguished engineer who led the technical work over eight sleepless weeks to bring OpenAI's models to Bedrock, said his own productivity as a software engineer has increased 10 to 20 times over the past year. When asked what excites him most about what comes next, he didn't talk about models or infrastructure. He talked about what happens when that same multiplier reaches the finance team, the product managers, the supply chain planners -- the millions of knowledge workers who have been watching the agentic revolution from the sidelines. "We had nothing eight weeks ago," he said, "and now we're here." If the next eight weeks move as fast, the sidelines may not exist for much longer.

AWS CEO Matt Garman sees huge business opportunity for Amazon in AI-powered software: 'Everything is going to be remade' | Fortune

AWS chief executive Matt Garman isn't losing any sleep over talk of the "SaaSpocalypse." In fact, he's so confident companies will continue to buy software-as-a-service in the age of AI that he's pushing Amazon Web Services into the SaaS business, and rolling out various products aimed directly at office workers and other professionals. On Tuesday AWS unveiled Amazon Quick, a desktop application that lets users interact with an AI chatbot to handle personal productivity tasks like creating work presentations and arranging meetings. The company also announced a trio of new Connect applications to help workers with tasks in specialized fields such as hiring, healthcare, and supply chain management. For the world's leading cloud computing provider, whose core business involves helping companies like Netflix, Adidas, and Pfizer run their websites and operations online, selling software for individual workers is quite a change of pace. In an interview with Fortune on Tuesday, Garman described it as a "huge business opportunity" for AWS and said the advent of agentic AI is what prompted the company to dive in. "As we look across applications, we see that so many applications are getting done with AI and agents. And we think that there is just such a massive change out there that everything is going to be remade," Garman said. "I don't think personal productivity has really been remade for the last 30 years," Garman said in reference to the new Quick application. Quick will be available to individual users even if they're not AWS customers, with both a free tier and a premium tier. "There are going to be millions of successful applications that people us; obviously the vast, vast majority of them will not be built by Amazon or AWS, but we think there are a handful of them that we can build that will be pretty successful and that customers will like," said Garman. AWS showed off the new products at an event in San Francisco Tuesday in which the company also announced details of a new partnership with OpenAI. For the first time, AWS business customers will be able to integrate OpenAI's AI models directly into their products and services. Until now, OpenAI's GPT models were only available via Microsoft's cloud thanks to an exclusive partnership that Microsoft and OpenAI struck several years ago. That agreement was revised this week, opening the door for AWS to include the latest GPT models and OpenAI's Codex coding tool for its cloud customers alongside other models such as Anthropic's Claude and Meta's Llama. While Garman would not provide details of the financial terms of AWS's new partnership with OpenAI, he noted that it includes a revenue share. Earlier this year, Amazon invested $50 billion in OpenAI, and the company has been working with OpenAI on training its models and in other areas. The product announcements come one day before Amazon is set to report its first-quarter results, which will take place after the close of market on Wednesday. AWS is Amazon's fastest-growing business segment, with revenue rising 20% to $128.7 billion in 2025, and the company's most profitable, earning $45.6 billion in operating income last year. Garman, who joined AWS as an intern in 2006, was appointed CEO of the business in May 2024. His leadership of Amazon's cloud business has coincided with the AI boom and the remarkable scramble among cloud providers, including Microsoft, Google, and Oracle, to spend eye-popping sums building data centers and other AI infrastructure. Amazon has said it plans to lay out $200 billion in capital expenditures this year, up more than 50% from its $131 billion in 2025 capex. Asked if he could have imagined such massive investments when he took the CEO reins two years ago, Garman said that AWS has always been in a capital-intensive line of business. "I don't know if I would have exactly expected we would be at the rate we are now, but it's heavily tied to how fast the business is growing," he said. "So the faster the business grows the more capex we need to spend to make sure we have capacity for customers. But if you look at the economics of AWS you're going to invest in that all day." Because of its experience and expertise operating data centers efficiently and at low cost, Garman said, AWS's move to offer customers AI-powered software like Quick and Connect products would not weigh on profit margins. "We get to run and benefit from all the efficiencies that we get from AWS," Garman said. "We think many of these could have higher margins than just the infrastructure, where you add continuous value on top of those."

Amazon Connect's second act: From contact center to agentic AI suite - SiliconANGLE

Amazon Connect's second act: From contact center to agentic AI suite It has been just under a decade since Amazon Web Services Inc. launched Amazon Connect, taking its own internal contact center-as-a-service solution and commercialized it. At the time, there were many doubts about whether it could succeed in a mature market with several established vendors. The company loaded Connect up with artificial intelligence features long before AI was cool, and a unique utilization-based pricing model to disrupt, and it rapidly gained traction. Today, it's the primary customer experience platform for many major brands, including Capital One, Hilton Hotels, State Farm and Air Canada. AWS is repositioning the Connect brand as a family of agentic AI solutions that integrate into business workflows, not just the contact center. The new portfolio comprises four products: Amazon Connect Decisions for supply chains, Amazon Connect Talent for high-volume hiring, Amazon Connect Customer for customer experience (the original Connect, rebranded), and Amazon Connect Health for healthcare delivery. As with Connect, these products are built on capabilities Amazon first used to run its own operations at massive scale, from optimizing a catalog of more than 400 million SKUs to hiring 250,000 seasonal workers in a single peak season. A key design tenet across the suite is what AWS calls "humorphism" - the idea that AI should behave like a teammate, not a traditional application with menus and forms. Instead of adding AI features to existing software, the Connect products are built from the ground up for agents that can reason, remember, and act while collaborating with humans. That shows up in patterns like agents proactively asking planners about upcoming promotions that could affect demand, or interviewing job candidates overnight and handing recruiters a curated brief in the morning. In our conversation, Pasquale DeMaio, vice president of Amazon Connect Customer and Talent, underscored that philosophy: The AI handles much of the screening and interviewing process, "but then moving forward after that, it hands off to a human recruiter," so people still make the final call. He was crystal clear on our call that the Amazon Connect portfolio isn't here to replace people but to let them work smarter and faster. Connect's evolution has been underway internally for some time. DeMaio told me it has "been over two years" since he last referred to Connect as a contact center, arguing that the market continued to pigeonhole the service as "just about pipes" even as Amazon shipped more AI-centric capabilities. Renaming the CX product Amazon Connect Customer is intended to make it unmistakable that "Connect is really an AI service." It's worth noting that this isn't about Amazon building speculative AI products and hoping customers will find a use for them. The company is productizing systems that already power core Amazon businesses: supply chain optimization powered by its SCOT foundation models, high-volume hiring tuned to its seasonal workforce, and healthcare workflows honed through One Medical and Amazon Pharmacy. As DeMaio put it, Amazon often "learns so much" and "does some amazing science" for internal tools, then spends time making them "enterprise-grade for a broader set of customers," which is the original Connect story. Amazon's history of taking internal platforms external is well-known -- AWS itself began as infrastructure for Amazon.com -- but the Connect family is a more targeted version of the same playbook. Internally, Amazon used its hiring science to quickly identify the right candidates, maintain a high performance bar and systematically reduce bias. The new Amazon Connect Talent essentially packages that operating model for customers. Because the tools are born in production, they start with clear outcome metrics: time-to-fill, offer-in-a-day targets, retention and evaluation consistency for Talent; forecast accuracy, exception resolution time and working capital impact for Decisions; and containment, handle time and NPS-style measures for Customer. DeMaio said the same science that lets Amazon "move very quick, but keep a very high bar for the hiring process" is what they're now offering to enterprises grappling with weeks-long hiring cycles. There's also a go-to-market benefit: each of these workloads can reach departments that historically would never buy a contact center, and then lead them back toward the broader Connect platform. DeMaio acknowledged this dynamic, telling me he believes Talent will be a "backdoor" into the customer experience side, even though it's intentionally sold as a standalone product that does not require adopting other parts of Connect. Among the new offerings, Amazon Connect Talent may be the clearest signal of how far Connect has moved from its contact center roots. Talent is aimed squarely at high-volume hiring, where organizations constantly trade off speed and quality. The workflow starts with an existing job description. AI agents generate a complete interview plan, including competencies, structured questions, and evaluation criteria, which recruiters can review and adjust. Candidates then interview on their own schedule, 24/7, via voice. The agent asks job-related questions, adapts to responses, and assembles a package of anonymized competency scores, transcripts, and notes for recruiters. DeMaio emphasized that this can compress hiring cycles from "a week or weeks" to "a day," driving "5x, 10x improvement" in time-to-offer for many high-volume roles. Equally important is the objectivity story. Candidate names and other identifying information are removed from recruiter dashboards, eliminating obvious bias vectors such as name, address, or accent. "You can never provably remove 100% of bias," DeMaio cautioned, but Amazon's goal is to give customers "good guardrails," visibility into where bias might be creeping in, and tools to "prevent it on the front end" while keeping hiring a "shared responsibility." For customers, the immediate benefit of Amazon Connect Talent is speed and scalability without surrendering control. Recruiters tune the experience up front, using prompts, job descriptions, or other data, and can adjust thresholds as they observe how competency scores translate into retention or performance for their specific roles. This also changes the recruiter's day. Instead of starting a week buried under unread applications, they begin with a curated pipeline, consistent scores, and full transcripts when detail is needed. DeMaio described it as a "fundamental sea shift" in which recruiters no longer need to be involved in every touchpoint, freeing them to focus on relationships rather than repetitive administrative work. Over time, customers can build a library of interview templates for different job types while letting the agentic layer handle execution. Even as Amazon expands into talent and healthcare, the rebranded Amazon Connect Customer remains the flagship for customer engagement. It now offers configuration tooling that enables business teams, not just developers, to stand up conversational experiences in weeks rather than months, covering identity verification, payments, recommendations and issue resolution. Enterprise customers like United Airlines have been able to go from concept to production in about three months, compared with six months or more with legacy stacks. Amazon Connect Decisions shows how Amazon is extending the same agentic pattern deeper into operations. Built on more than 25 specialized supply chain tools and SCOT-backed forecasting models, Decisions continuously generates and tunes demand forecasts, then triages thousands of alerts into a small set of prioritized exceptions, each with root-cause analysis and suggested resolutions. Customers such as Wells Vehicle Electronics and TVS Motors are already using it to shift from weeks-long planning cycles to adjustments measured in minutes. Taken together, the new Connect family is AWS' answer to a key enterprise question: how do you operationalize AI beyond pilots in the contact center? By anchoring each product in a real business function and Amazon's operational history, AWS is positioning Connect less as a channel-centric platform and more as a suite of AI teammates that sit wherever work actually happens. DeMaio told me this rebrand is about "resetting the idea of what Connect is," building on a decade-long brand that customers "trust and love," and using it to "bring AI to enable AI as teammates to help people be better, not to remove connection." If AWS executes, Connect may come to be known less as Amazon's contact center and more as Amazon's application layer for agentic AI across the enterprise.

Amazon's AWS Bets Big On Agentic AI To Reinvent Software -- CEO Matt Garman Says 'Everything Is Going To Be

AWS Unveils AI Productivity Tools On Tuesday, AWS unveiled new AI-focused products, including Amazon Quick, a desktop assistant designed to help users complete productivity tasks such as creating presentations and scheduling meetings. It also introduced new Amazon Connect applications tailored for industries such as healthcare, hiring, and supply chain management. In an Interview with Fortune, Garman said the rise of "agentic AI" is driving a major reinvention of software. "We think that there is just such a massive change out there that everything is going to be remade." "I don't think personal productivity has really been remade for the last 30 years," Garman added, describing Quick as part of AWS's push into AI-driven tools that can be used even by non-AWS customers. AWS also announced a partnership with OpenAI, giving customers access to models like GPT and Codex through its cloud infrastructure, expanding options alongside systems from Anthropic and Meta. "We think there are a handful of them that we can build that will be pretty successful and that customers will like," Garman said, noting that most AI software innovation will come from outside Amazon. Amazon Accelerates AI Expansion Across Key Businesses Amazon expanded its AI efforts across hiring automation, cloud computing performance and infrastructure spending. Amazon launched Connect Talent, an AI hiring tool that automated candidate screening and interviews for high-volume recruitment, with applicants notified when AI was used. Earlier, AWS also partnered with Cerebras Systems to speed up AI processing by combining chips and splitting workloads between input and output systems. The company defended rising AI capital spending, saying customer demand was strong and AWS's profitability remained solid despite higher costs, with executives expecting efficiencies to offset future spending. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Amazon Expands Connect Service to Cover Supply Chains and HR | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. The new artificial intelligence (AI) tools, announced by the company's Amazon Web Services arm Tuesday (April 28), are aimed at logistics workers, human resources, customer service departments, along with a previously announced healthcare offering. "These new Connect solutions draw on our expertise incorporating agents throughout Amazon's operations," the company said, noting the breadth of its experience in supply chain, hiring, custom interactions and its health and pharmacy business. "We've built AI systems not just to think about these challenges but to solve them in the real world, at scale, every single day." A central component of this expansion is Amazon Connect Decisions, a tool designed to manage supply chain logistics and forecasting. The company notes that supply chain disruptions can take weeks to resolve due to fragmented data systems and manual spreadsheet coordination, while its solution uses more than 25 specialized supply chain tools and foundation models from Amazon's Supply Chain Optimization Technologies (SCOT) to automate these processes Amazon Connect Talent is modeled after the company's internal hiring processes, the release added, citing the company's annual recruitment of hundreds of thousands of workers for the holiday shopping season. Amazon Connect Customer -- previously known simply as Amazon Connect -- has been updated to include "new configuration capabilities that enable organizations to set up conversational AI in weeks, not months, and configure experiences without technical expertise." Amazon Connect Health was introduced in March to automate administrative tasks for healthcare providers. As covered here, this tool handles patient verification, scheduling, medical histories, documentation and coding. The new offerings come as AI agents play an increasingly prominent role in the workplace, as PYMNTS wrote earlier this week. Agentic AI "is starting to move from conference-room promise to operating-room reality in financial services, where banks, insurers and asset managers are testing software agents on the manual work that slows down decisions," the report said. The report cited recent findings from the likes of Snowflake, KPMG and The Economist based around the same theme: the first major gains are likely to be the result of assigning agents tightly controlled tasks like gathering data, checking documents, routing approvals and preparing recommendations. "The larger shift is not simply faster automation," PYMNTS wrote. "It is a new model for financial work, one in which firms use stronger data foundations, clearer governance and human oversight to turn fragmented processes into more continuous workflows."

Amazon Web Service Does an Agentic Shift into the Application Layer

Anurag Agarwal analyses how the ecosystem has changed forever from being a platform selling the cloud with multiple vendor solutions to one with managed AI agents Earlier this week, Amazon Connect was rebranded into a four-product family, and launched as the Amazon Quick app on the desktop - the culmination of an exercise of accepting that infrastructure alone cannot solve the enterprise activation void. Also AWS had introduced managed AI agents for OpenAI within Amazon Bedrock must recently. And it is doing so armed with a moat that no SaaS incumbent - not Salesforce, not Workday, not Epic - can replicate: the operational record of having actually run the world's largest retailer, logistics network, hiring engine, and primary care practice. This is not a feature update. It is a category change, says Anurag Agrawal, CEO of research company TechAisle. This is a paradigm shift from an ecosystem that stood the test of time for two decades. In it, "AWS sold the substrate - compute, storage, networking, databases, and models" while the software vendors built the experiences that customers actually used. For two decades, the bargain between AWS and the software industry was clear and mutually profitable. "The hyper-scaler captured rent on the floor, the vendors captured rent on the ceiling," the paper says. And, every Salesforce, Workday, ServiceNow, Epic, and SAP transaction reinforced this division of labour. In the research note, Agrawal notes that Amazon's announcement sounded boring and not like a highly loaded strategic announcement. Amazon Connect is now a family of agentic solutions to transform entire business functions. The Connect family will house four products - Customer AI (the original contact-centre solution), Decisions (supply chain), Talent (hiring), and Health (clinical workflow) - each one introducing an agentic alternative to established SaaS categories, is what they said. But, the signal is unmistakable in that it describes what AWS chooses to absorb rather than sparing effort to build anew. Connect Decisions is, in the words of AWS's own product leadership, the next generation of AWS Supply Chain - the prior product has been "essentially assimilated," which is the same playbook AWS used with Amazon SageMaker AI. Take a workbench tool, rebuild it as an industrial system, reposition the category. Except this time, the categories are not "machine learning platforms." They are enterprise hiring, clinical documentation, and supply chain planning, is how Agrawal describes this process. The vendors who traditionally own those categories are publicly traded SaaS giants, and AWS has just fundamentally altered their competitive baseline. While AWS will undoubtedly continue to host and support these competitors, the philosophical shift is unambiguous: the application layer is no longer a passive ecosystem. It is an active arena for AWS innovation. Of course, there are issues that could manifest later. For example it is unclear how AWS plans to differentiate in domains where the incumbents have spent two decades building depth. The answer could be "operational provenance" - the strategic asset of having actually run the workflow at planetary scale that builds capability to encode the experience into software. It is quite obvious that the this week's announcements signal the start of the "Application Reabsorption Era where hyper-scalers, having spent two decades enabling the SaaS economy, now begin to selectively reclaim the highest-value layers. "AWS will not absorb everything. It will absorb the workflows where its own operational data gives it an unfair advantage. That list is longer than most SaaS executives are prepared to acknowledge," says Agrawal. You can read the entire analytical insight right here. The page also allows a download of the said story.